Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Assessment of Renewable Energy Resources with Remote Sensing
| Assessment of Renewable Energy Resources with Remote Sensing |
| Autore | Martins Fernando Ramos |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (244 p.) |
| Soggetto topico | Research & information: general |
| Soggetto non controllato |
artificial neural networks
Baltic area climate cloud cloud coverage cloud detection coastal wind measurements coastline computational design method convection CSP plants data processing digitized image processing electrical resistivity tomography extreme value analysis feature engineering feature importance forecasting geophysical prospecting geothermal energy GES-CAL software global radiation graphical user interface software Hazaki Oceanographical Research Station hydropower reservoir image processing lake breeze influence light gradient boosting machine machine learning machine learning techniques metaheuristic multistep-ahead prediction parameter extraction passive design strategy photovoltaic power plant plan position indicator point cloud data potential well field location remote sensing remote sensing data acquisition renewable energy resource assessment and forecasting satellite scanning LiDAR scatterometer shading envelopes sky camera smart island solar energy solar energy resource solar irradiance enhancement solar irradiance estimation solar irradiance forecasting solar photovoltaic solar radiation forecasting statistical analysis surface solar radiation time domain electromagnetic method total sky imagery velocity volume processing voxel-design approach whale optimization algorithm wind speed |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557427903321 |
Martins Fernando Ramos
|
||
| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems
| Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems |
| Autore | Li Chaoshun |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (212 p.) |
| Soggetto topico |
Physics
Research and information: general |
| Soggetto non controllato |
'S' characteristics
1D-3D coupling model active power anomaly detection approximate entropy cascaded reservoirs change point detection chaotic particle swarms method comprehensive deterioration index cosine similarity degradation trend prediction doubly-fed variable speed pumped storage power station doubly-fed variable-speed pumped storage ensemble empirical mode decomposition facility agriculture fractional order PID controller (FOPID) gated recurrent unit high proportional renewable power system Hopf bifurcation hybrid system hydraulic oil viscosity hydraulic PTO hydro power hydropower units light gradient boosting machine long and short-term neural network low water head conditions maximal information coefficient maximum information coefficient multi-objective optimization noise reduction nonlinear modeling nonlinear pump turbine characteristics operation strategy parameter sensitivity power yield pressure pulsation pumped storage unit pumped storage units pumped storage units (PSUs) reliability seasonal price sensitivity analysis sparrow search algorithm stability analysis stochastic dynamic programming (SDP) successive start-up thermal-hydraulic characteristics transition stability variational mode decomposition wave energy converter |
| ISBN | 3-0365-5838-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910637780603321 |
|
Li Chaoshun
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||